Network densification becomes inevitable due to rapidly increasing mobile data traffic in the evolution of future cellular networks. Therefore, Heterogeneous Wireless Networks eliminate the challenges that are not covered in 4G-Long Term Evolution. The extensive contribution of the proposed work is to develop a cluster based algorithm that establishes the maximum node connections in the heterogeneous wireless network and also to implement effective Multi-User Generalized Frequency Division Multiplexing in the physical layer for future wireless communications. The presence of unconnected nodes (Base Stations) in the wireless network reduces the network efficiency and coverage capacity. Whenever a wireless device is connected to at least one isolated neighbor node (BS), it acts as a Virtual Clustered Head based on shortest path node and residual energy of the node. A Virtual Cluster (VC) based multipath routing is implemented for Heterogeneous Networks to maximize the Energy Efficiency (EE), Spectral Efficiency (SE), Channel Capacity (CC), and Network Capacity (NC) and minimize the Bit Error Rate and latency under different constraints in the network. The simulation results with GFDM modulation shows the improvement in the network performance and compared with existing OFDM results.

Performance Analysis of GFDM Modulation in Heterogeneous Network for 5G NR

Generalized frequency-division multiplexing (GFDM) is one of the promising multi-carrier modulation schemes suitable for next-generation wireless communication systems. The main characteristic of GFDM is the flexible time-frequency structure of data blocks. However, this degree of freedom is obtained at the cost of loss of sub-carrier orthogonality, which leads to self-interference. In this paper, we propose a new model that classifies the GFDM self-interferences into two independent categories as inband and adjacent sub-carriers interferences and show their corresponding mathematical formulations. Building on this model, we propose a successive interference cancellation (SIC) technique with low complexity to eliminate these self-interference effectively. The main distinct feature of our proposed technique is its low computational complexity compared to similar interference cancellation techniques. Our analytical findings and numerical experiments indicate that the proposed model and SIC technique considerably improve the system performance in terms of bit error rate (BER) and signal to interference ratio (SIR). We also show that the results of our analytical findings are in good agreement with those of computer simulations.

https://ieeexplore.ieee.org/ielx7/6287639/6514899/09756522.pdf

Novel Successive Interference Cancellation (SIC) With Low-Complexity for GFDM Systems

Generalized frequency-division multiplexing (GFDM) is one of the promising multi-carrier modulation schemes suitable for next-generation wireless communication systems. The main characteristic of GFDM is the flexible time-frequency structure of data blocks. However, this degree of freedom is obtained at the cost of loss of sub-carrier orthogonality, which leads to self-interference. In this paper, we propose a new model that classifies the GFDM self-interferences into two independent categories as inband and adjacent sub-carriers interferences and show their corresponding mathematical formulations. Building on this model, we propose a successive interference cancellation (SIC) technique with low complexity to eliminate these self-interference effectively. The main distinct feature of our proposed technique is its low computational complexity compared to similar interference cancellation techniques. Our analytical findings and numerical experiments indicate that the proposed model and SIC technique considerably improve the system performance in terms of bit error rate (BER) and signal to interference ratio (SIR). We also show that the results of our analytical findings are in good agreement with those of computer simulations. 

/pdf/novel-successive-interference-cancellation-sic-with-low-10r51rzj.pdf

In 5G network, resource allocation for the cell edge users is the major challenge. To address this challenge, we present GFDM (Generalized Frequency Division Multiplexing) for the physical layer of 5G wireless networks is a non orthogonal waveform with circularly pulse shaped mechanism. This mechanism is also used for resource allocation. In this paper, to allocate the weights on the filter bank of GFDM for cell edge users, an optimized Deep Neural Network (DNN) is presented in this paper. To enhance the performance of the DNN, weight parameters of it are optimized using Rain Optimization Algorithm (ROA). Using this proposed ROA based DNN, weight resources are allocated to the cell edge users optimally. Simulation results shows that the performance of the proposed resource allocation outperforms the conventional resource allocation in terms of normalized cell throughput.

A Novel Approach to the Resource Allocation for the Cell Edge Users in 5G

In the current smart era of 5G, cellular devices and mobile data have increased exponentially. The conventional network deployment and protocols do not fulfill the ever-increasing demand for mobile data traffic. Therefore, ultra-dense networks have widely been suggested in the recent literature. However, deploying an ultra-dense network (UDN) under macro cells leads to severe interference management challenges. Although various centralized and distributed clustering methods have been used in most research work, the issue of increased interference persists. This paper proposes a joint small cell power control algorithm (SPC) and interference-managed hybrid clustering (IMHC) scheme, to resolve the issue of co-tier and cross-tier interference in the small cell base station cluster tiers. The small cell base stations (SBSs) are categorized based on their respective transmitting power, as high-power SBSs (HSBSs) and low-power SBSs (LSBSs). The simulation results show that by implementing the IMHC algorithm for SBSs in a three-tier heterogeneous network, the system throughput is improved with reduced interference.

/pdf/an-interference-managed-hybrid-clustering-algorithm-to-39m3zwty.pdf

R. Anil Kumar

Papers

Performance Analysis of GFDM Modulation in Heterogeneous Network for 5G NR

Out-of-Band Radiation, PAPR and SER Analysis for Future Wireless (5G) Communications